Triple

T11666922
Position Surface form Disambiguated ID Type / Status
Subject The Big Store E277272 entity
Predicate screenwriter P2831 FINISHED
Object Hal Fimberg E845359 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Hal Fimberg | Statement: [The Big Store, screenwriter, Hal Fimberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hal Fimberg
Context triple: [The Big Store, screenwriter, Hal Fimberg]
  • A. Hal Fimberg chosen
    Hal Fimberg was an American screenwriter and producer best known for his work on 1960s spy spoof films and other Hollywood genre movies.
  • B. Leon Feldhendler
    Leon Feldhendler was a Polish Jewish resistance leader and Holocaust survivor best known for co-organizing the 1943 prisoner uprising at the Sobibor extermination camp.
  • C. Steven Fierberg
    Steven Fierberg is an American cinematographer known for his work on feature films and television series, including the romantic drama "Love & Other Drugs."
  • D. Howard Bilerman
    Howard Bilerman is a Canadian drummer, audio engineer, and record producer best known for his work with Arcade Fire and numerous influential indie rock recordings.
  • E. Allen Boretz
    Allen Boretz was an American playwright and screenwriter best known for his work in mid-20th-century theater and film comedies.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d6aafd0a448190b44da30af8c6c519 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a43f438081909da476294a057c38 completed April 10, 2026, 7:18 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7941721d08190900ca872503055db completed May 3, 2026, 6:29 p.m.
Created at: April 8, 2026, 9:39 p.m.